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All Journal Natural Sciences Engineering and Technology Journal Sriwijaya Journal of Obstetrics and Gynecology Enigma in Education Enigma in Law
Gayatri Putri
Department of Library and Informatics Science, Enigma Institute, Palembang, Indonesia
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 1 
Building a Profession from the Ground Up: A Longitudinal Study of Teacher Professional Development and Pedagogical Innovation in Papuan Private Schools Iis Sugandhi; Arya Ganendra; Aaliyah El-Hussaini; Gayatri Putri; Evelyn Wang; Anita Havyasari; Muhammad Hasan
Enigma in Education Vol. 3 No. 1 (2025): Enigma in Education
Publisher : Enigma Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61996/edu.v3i1.90

Abstract

Teacher quality is the most significant school-based determinant of student success, yet fostering professional excellence in remote and culturally diverse regions like Papua, Indonesia, presents profound challenges. Private schools often fill critical educational gaps but their teachers can be professionally isolated. This study addressed the gap in long-term, evidence-based research on teacher professional development (TPD) in this unique context. A three-year (2021-2024) concurrent mixed-methods longitudinal study was conducted. The study involved 50 teachers from a network of five private schools in urban, semi-rural, and remote highland regions of Papua. A comprehensive TPD program, focusing on student-centered learning and culturally responsive pedagogy, was implemented. Quantitative data were collected annually using the Teacher Pedagogical Knowledge Test (TPKT), the Teacher Self-Efficacy Scale (TSES), and a structured Classroom Observation Protocol. Qualitative data were gathered through semi-structured interviews, teacher reflective journals, and focus group discussions with Professional Learning Communities (PLCs). Quantitative data were analyzed using repeated measures ANOVA, while qualitative data were analyzed thematically. The longitudinal quantitative analysis revealed statistically significant improvements across all three years. Mean TPKT scores increased from 48.5 (SD=11.2) at baseline to 79.8 (SD=8.5) at endline (F(2, 98) = 157.2, p <0.001). Teacher self-efficacy scores also showed significant growth (F(2, 98) = 112.9, p <0.001). Classroom observations confirmed a marked shift from teacher-centered to student-centered practices. Qualitative findings identified three core themes: (1) "From Transmission to Facilitation: A Pedagogical Awakening," detailing the shift in teachers' core beliefs about learning; (2) "The Power of the Collective," highlighting the crucial role of PLCs in sustaining motivation and collaborative problem-solving; and (3) "Navigating the Cultural Interface," illustrating the teachers' journey in adapting curriculum to be more culturally responsive. In conclusion, sustained, context-specific, and collaborative TPD can foster profound and lasting improvements in teacher knowledge, self-efficacy, and classroom practice, even in highly challenging environments. The findings advocate for a shift away from isolated, short-term workshops towards integrated, long-term models that prioritize peer collaboration and cultural relevance, revealing a clear pathway from knowledge acquisition to a transformed professional identity.
Effectiveness of an Automated Feedback System on Creative Writing and Scientific Translation Skills Among Undergraduate Students: A Quasi-Experimental Study Danila Adi Sanjaya; Gayatri Putri
Enigma in Education Vol. 4 No. 1 (2026): Enigma in Education
Publisher : Enigma Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61996/edu.v4i1.123

Abstract

This quasi-experimental study investigates the effectiveness of an automated feedback system (AFS) on creative writing skills (CWS), scientific translation skills (STS), and writing self-efficacy (WSE) among undergraduate students. Participants comprised 136 students (experimental group: n = 68; control group: n = 68) from the Department of English Education at a public university in Palembang, Indonesia, enrolled in Writing and Translation courses during a 10-week intervention period. The experimental group received automated feedback through an integrated computer-assisted language learning platform, while the control group received conventional instructor-provided feedback. Pre- and post-test data were analyzed using Analysis of Covariance (ANCOVA), with large effect sizes observed across all dependent variables: creative writing skills (d = 1.84, 95% CI [1.38, 2.30], p < 0.001); scientific translation skills (d = 2.08, 95% CI [1.62, 2.54], p < 0.001); and writing self-efficacy (d = 1.94, 95% CI [1.49, 2.39], p < 0.001). Results demonstrate that automated feedback systems significantly enhance both skill development and learner confidence in academic writing contexts, particularly for skill-intensive tasks requiring iterative practice. The study also underscores the importance of combining automated feedback with periodic instructor guidance and peer collaboration.
Deep learning-assisted digital VIA via telemedicine and HPV self-sampling for CIN2+ detection in remote archipelago women: a prospective diagnostic accuracy study Theresia Putri Sinaga; Nur Diana; Firman Hadi; Gayatri Putri
Sriwijaya Journal of Obstetrics and Gynecology Vol. 4 No. 1 (2026): Sriwijaya Journal of Obstetrics & Gynecology
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjog.v4i1.302

Abstract

Background: Cervical cancer disproportionately burdens women in low- and middle-income countries, where archipelagic geography and colposcopist shortages obstruct screening. Human papillomavirus (HPV) self-sampling is highly sensitive but poorly specific, generating colposcopy referrals that exceed remote-area capacity. Objective: To evaluate whether deep-learning (DL)-assisted digital visual inspection with acetic acid (VIA), delivered by telemedicine, can triage HPV-positive women and detect high-grade cervical intraepithelial neoplasia (CIN2+). Methods: In a prospective, double-blind, STARD-compliant diagnostic accuracy study, 642 women aged 30–50 years at an urban tertiary referral hospital (Center A) and five remote community health centers (Region B) in an Indonesian archipelago province underwent HPV-DNA self-sampling and smartphone-captured digital VIA analyzed by a MobileNetV2 convolutional neural network. All participants received colposcopy-directed biopsy as the reference standard, eliminating verification bias. Metrics used Wilson 95% confidence intervals (CI); multivariable logistic regression and decision-analytic triage metrics were derived. Results: CIN2+ prevalence was 13.1% (95% CI 10.7–15.9). DL-assisted VIA achieved sensitivity 91.7% (95% CI 83.8–95.9), specificity 88.4% (85.4–90.8), and AUC 0.93, exceeding human-read VIA (sensitivity 67.9%). HPV self-sampling was most sensitive (95.2%) but least specific (81.5%). A sequential HPV→DL-VIA pathway raised specificity to 95.7% and positive predictive value to 75.5%, reducing colposcopy referrals by 46.4% and unnecessary referrals by 76.7% (number-needed-to-screen 7.6). HPV positivity dominated the multivariable model (adjusted OR 91.5, 95% CI 32.7–256.2, p<0.001; Nagelkerke R² 0.50). Conclusion: Telemedicine-delivered, DL-assisted VIA is an accurate triage for HPV-positive women that conserves scarce colposcopy capacity while preserving CIN2+ detection. This decentralized two-step pathway is a scalable strategy for advancing cervical-cancer elimination in geographically isolated populations.
Zombie Norms in Indonesian Regional Law: Measuring Vertical Disharmony with the Job Creation Law Across Three Regulatory Domains Andi Fatihah Syahrir; Gayatri Putri; Henrietta Noir
Enigma in Law Vol. 3 No. 2 (2025): Enigma in Law
Publisher : Enigma Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61996/law.v3i2.128

Abstract

The Job Creation Law (Law No. 11 of 2020, reconstituted as Law No. 6 of 2023) reorganised Indonesian business licensing, spatial-use control, and regional levies, abolishing a generation of sub-national instruments; yet harmonisation of the regional legislative stock has never been measured across domains. Six binary indicators of disharmony — obsolete legal basis, regulation of an abolished instrument, absence of new-regime terminology, pre-reform enactment still in force, a levy attached to an abolished instrument, and no post-2020 amendment or repeal — were aggregated into a 0–6 index. Eighty regional regulations (Perda) from seventy regions, enacted 2001–2025, were coded from official register metadata, each record carrying its verbatim legal-basis citation so that every coding decision is auditable. Seventy-seven instruments (96.3%) remain in force, at a mean index of 4.29 (SD 1.73). Disharmony is a legacy phenomenon: pre-reform instruments scored 5.22 (SD 0.77) against 1.82 (SD 0.91) post-reform (Welch t(33.2) = 15.60, p < 0.001, d = 4.20), an effect surviving controls for domain and tier (b = −3.24; R² = 0.808), while domains did not differ (H = 5.66, p = 0.059). Decisively, absence of post-2020 legislative action alone failed to discriminate between cohorts (Fisher's p = 1.00): regions draft new law correctly but almost never reopen the stock. Five instruments still rest on the colonial Hinder Ordonnantie of 1926. The failure is one of regulatory stock management, traceable to the removal of executive review of Perda in 2017 without substitution, and calls for statutory sunset rules rather than administrative annulment.
An In-Silico Investigation of Machine Learning for Integrating Genomic and Digital Biomarker Data in Cardiovascular Risk Stratification Immanuel Simbolon; Cindy Susanti; Gayatri Putri; Karina Chandra; Muhammad Yoshandi; Daniel Hilman Maulana
Natural Sciences Engineering and Technology Journal Vol. 5 No. 2 (2025): Natural Sciences Engineering and Technology Journal
Publisher : HM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37275/nasetjournal.v5i2.71

Abstract

Conventional models for stratifying cardiovascular disease (CVD) risk have limitations. The integration of static genomic data and dynamic digital biomarkers from wearable technology holds theoretical promise, but its potential quantitative impact remains poorly defined. This study aimed to develop and validate an in-silico framework to quantify the theoretical maximum predictive gain of an integrated risk model under idealized conditions. We developed a sophisticated data generating process (DGP) to create a synthetic dataset of 5,000 individuals. The DGP incorporated demographic and clinical variables with distributions and correlations based on epidemiological literature. It included a simulated polygenic risk score (PRS) for coronary artery disease and advanced digital biomarkers derived from wireless health monitoring data, such as heart rate variability (HRV) and time in moderate-to-vigorous physical activity (MVPA). The 10-year risk of Major Adverse Cardiovascular Events (MACE) was generated via a defined logistic function incorporating these variables plus stochastic noise. We compared the performance of the ACC/AHA Pooled Cohort Equations (PCE) against several machine learning models (Logistic Regression, Random Forest, XGBoost) using the area under the receiver operating characteristic curve (AUC-ROC), precision, recall, and F1-score. In this simulated environment, the integrated XGBoost model achieved near-optimal predictive performance with an AUC-ROC of 0.92 (95% CI, 0.90-0.94), significantly outperforming the benchmark PCE model (AUC-ROC 0.76; 95% CI, 0.73-0.79; p < 0.001). The inclusion of the PRS and, most notably, dynamic digital biomarkers like HRV, provided substantial incremental improvements in risk discrimination over traditional factors alone. In conclusion, this in-silico study demonstrates the substantial theoretical potential of integrating genomic and advanced digital biomarker data through machine learning for CVD risk stratification. While these idealized results are not directly generalizable, they provide a quantitative rationale for pursuing real-world data collection and validation studies. This work establishes a methodological proof-of-concept and highlights the potential for a paradigm shift toward more dynamic and personalized cardiovascular risk assessment.
Co-Authors Aaliyah El-Hussaini Andi Fatihah Syahrir Anita Havyasari Arya Ganendra Cindy Susanti Daniel Hilman Maulana Danila Adi Sanjaya Evelyn Wang Firman Hadi Henrietta Noir Iis Sugandhi Immanuel Simbolon Karina Chandra Muhammad Hasan Muhammad Yoshandi Nur Diana Theresia Putri Sinaga